No description available.

This thesis presents an inspection method based on RGB-D profiling for the rail industry. The proposed approach uses inexpensive RGB-D cameras to generate color and geometrical information of the observations, and stitches each consecutive scan from the sensor to form a map, provided that the two scans contain the information from the same observation. Using a technique known as pairwise registration, the errors between these consecutive scans are minimized using error minimization algorithms such as Iterative Closest Point and Normal Distributions Transform. Once the error between each consecutive scan is minimized, the scans are then converted into a global co-ordinate frame work to form a global map of all the added scans. The proposed approach could be used as a map-based identification technique by comparing the past global map to newly acquired scans while also reducing computation time effectively. The effectiveness of this approach is demonstrated by developing a system that uses multiple RGB-D cameras to detect railway defects such as spikes. The applicability of the proposed approach to other applications is then evaluated by profiling long lengths of road. / Master of Science

Submitted by Claudia Rocha (claudia.rocha@udesc.br) on 2017-12-05T12:41:21Z No. of bitstreams: 1 PGCS15MA124.pdf: 1312847 bytes, checksum: 750d88452b24e573464fff88790dbef6 (MD5) / Made available in DSpace on 2017-12-05T12:41:21Z (GMT). No. of bitstreams: 1 PGCS15MA124.pdf: 1312847 bytes, checksum: 750d88452b24e573464fff88790dbef6 (MD5) Previous issue date: 2015-05-15 / The soil organic matter (SOM) is formed by a set of chemical compounds which have different decomposition rates and products of these processes result as the main source of sulfur, phosphorus and nitrogen into the soil. Because of its great importance to the ground, it is of utmost importance to quantify MOS content. Its composition consists of carbon (C), hydrogen (H), oxygen (O), nitrogen (N), phosphorus (P) and sulfur (S), among others, it is difficult to determine its content. Most analytical techniques measure only carbon and estimate the MOS by a conversion factor. The study aimed to develop an analytical method for quantification of soil organic matter by means of a colorimetric method based on image analysis. The proposed method used the carbon oxidation process of Walkley-Black methodology and the resulting solutions were inserted into spectrophotometer cells for a smart phone equipped with a digital camera with a CCD detector (charge coupled device) register the images. These were treated with ImageJ software and the image of each solution has been selected from an area in which 100x100p were extracted RGB intensities (Red, Green and Blue colors, designs, especially for 8-bit data). We analyzed the RGB values and its relations with the MOS concentrations, resulting that the RED channel showed the best relationship with the organic matter content. The data were modeled by a linear regression (ARED = 0.1222 MOS - 0.1621; R² = 0.9934 and p <0.05) and it was possible to build a model that relates the color intensity with concentration. The proposed method showed accuracy of approximately 71% using a standard soil sample (LUFA Speyer - type 2.2), similar to the result obtained with the method currently used (Walkley-Black) which was 74% / A matéria orgânica do solo (MOS) é formada por um conjunto de compostos químicos que possuem diferentes taxas de decomposição, e os produtos desses processos resultam como fontes principais de enxofre, fósforo e nitrogênio para o solo. Devido a sua grande importância para o solo, é de extrema importância a quantificação do teor da MOS. Como a sua composição consiste em carbono (C), hidrogênio (H), oxigênio (O), nitrogênio (N), fósforo (P) e enxofre (S), dentre outros, torna-se difícil a determinação do seu teor. A maioria das técnicas analíticas mensuram apenas carbono e estimam a MOS por um fator de conversão. A pesquisa teve por objetivo o desenvolvimento de uma metodologia analítica para quantificação de matéria orgânica do solo por meio de um método colorimétrico baseado em análise de imagens. O método proposto utilizou o processo de oxidação de carbono da metodologia Walkley-Black e as soluções resultantes foram inseridas em celas espectrofotométricas para que um smartphone equipado com uma câmera digital, com um detector CCD (charge coupled device), registre as imagens. Estas foram tratadas com o software ImageJ e na imagem de cada solução foi selecionado uma área de 100x100p no qual extraíram-se as intensidades RGB (Red, Green e Blue, modelos de cores, especialmente para dados de 8 bits). Analisou-se os valores RGB e suas relações com as concentrações de MOS, resultando que o canal RED apresentou a melhor relação com o teor de matéria orgânica. Os dados foram modelados por meio de uma regressão linear (ARED = 0,1222 MOS – 0,1621; R² = 0,9934 e p < 0,05) e assim foi possível a construção de um modelo que relaciona a intensidade de cor com a concentração. O método prposto apresentou exatidão de aproximadamente 71% usando uma amostra de solo padronizada (LUFA Speyer – tipo 2.2), similar ao resultado obtido com o método usado atualmente (Walkley-Black) que foi de 74%

Submitted by EVERTON SIMÕES DA MOTTA (evmotta08@gmail.com) on 2017-01-05T13:08:55Z No. of bitstreams: 1 DissertacaoFinalCorrigida-v5.pdf: 7335404 bytes, checksum: fa4ba2ff69cd4d2dd72b1b5cb475111b (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2017-01-09T17:01:51Z (GMT) No. of bitstreams: 1 motta_es_me_rcla.pdf: 7335404 bytes, checksum: fa4ba2ff69cd4d2dd72b1b5cb475111b (MD5) / Made available in DSpace on 2017-01-09T17:01:51Z (GMT). No. of bitstreams: 1 motta_es_me_rcla.pdf: 7335404 bytes, checksum: fa4ba2ff69cd4d2dd72b1b5cb475111b (MD5) Previous issue date: 2016-12-22 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Sistemas de captura de movimentos humanos vêm sendo cada dia mais estudados, tanto pela área de Visão Computacional, quanto por grandes empresas do setor de entretenimento. São sistemas capazes de rastrear a posição e orientação das articulações do corpo e sua trajetória no espaço durante um intervalo de tempo. São utilizados em diversas aplicações, tais como em jogos digitais, animação de personagens virtuais para cinema e televisão, reconhecimento gestual, medicina de reabilitação, e outras. O surgimento de novos dispositivos de baixo custo e boa resolução que fornecem informações de profundidade, tem motivado novas pesquisas para a utilização dos mesmos. No entanto, sistemas que se baseiam somente em informações de profundidade (geralmente sistemas em tempo real) não apresentam uma alta acurácia no rastreamento do movimento. Considerando este contexto, o presente trabalho teve como objetivo principal, o desenvolvimento de um método de captura de movimentos humanos utilizando único sensor RGB-D, combinando informações de textura da imagem e de profundidade, que são associados a um esqueleto virtual, conseguindo-se uma maior acurácia em comparação com os métodos baseados apenas em profundidade. Tal método não visa aplicações de tempo real, mas sim, uma maior acurácia em comparação com os métodos baseados apenas em profundidade. / Human motion capture systems are being increasingly studied, in the area of computer vision and also by major entertainment industries. These systems are able to track the position and orientation of joints of the body and its trajectory in space over a period of time. They are used in various applications such as digital games, animation of virtual characters for film and television, gesture recognition, medical rehabilitation, etc. The emergence of new low-cost and good resolution devices that provide depth information has prompted new research. However, systems that are based only on depth information (usually real-time systems) do not present a high accuracy in movement tracking. Considering this context, this thesis project presents the development of a method for capturing human movements using only one RGB-D sensor, combining captured texture from the image and depth information in order to obtain a higher accuracy, which are associated with a virtual skeleton. This method is not intended for real-time applications, but those that require greater accuracy, such as the animation of virtual characters in video and medical rehabilitation.

Submitted by Nayara Passos (nayara.passos@ufpe.br) on 2015-03-12T13:53:20Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) TESE João Paulo Silva do Monte Lima.pdf: 5689244 bytes, checksum: e6e2c3f1da85d18b6bb7049e458f50e7 (MD5) / Made available in DSpace on 2015-03-12T13:53:20Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) TESE João Paulo Silva do Monte Lima.pdf: 5689244 bytes, checksum: e6e2c3f1da85d18b6bb7049e458f50e7 (MD5) Previous issue date: 2014 / CAPES , CNPq / Sistemas de Realidade Aumentada são capazes de realizar registro 3D em tempo real de objetos virtuais e reais, o que consiste em posicionar corretamente os objetos virtuais em relação aos reais de forma que os elementos virtuais pareçam ser reais. Uma maneira bastante popular de realizar esse registro é usando detecção e rastreamento de objetos baseado em vídeo a partir de marcadores fiduciais planares. Outra maneira de sensoriar o mundo real usando vídeo é utilizando características naturais do ambiente, o que é mais complexo que usar marcadores planares artificiais. Entretanto, detecção e rastreamento de características naturais é mandatório ou desejável em alguns cenários de aplicação de Realidade Aumentada. A detecção e o rastreamento de objetos a partir de características naturais pode fazer uso de um modelo 3D do objeto obtido a priori. Se tal modelo não está disponível, ele pode ser adquirido usando reconstrução 3D, por exemplo. Nesse caso, um sensor RGB-D pode ser usado, que se tornou nos últimos anos um produto de fácil acesso aos usuários em geral. Ele provê uma imagem em cores e uma imagem de profundidade da cena e, além de ser usado para modelagem de objetos, também pode oferecer informações importantes para a detecção e o rastreamento de objetos em tempo real. Nesse contexto, o trabalho proposto neste documento tem por finalidade investigar o uso de sensores RGB-D de consumo para detecção e estimação de pose de objetos a partir de características naturais, com o propósito de usar tais técnicas para desenvolver aplicações de Realidade Aumentada. Dois métodos baseados em retificação auxiliada por profundidade são propostos, que transformam características extraídas de uma imagem em cores para uma vista canônica usando dados de profundidade para obter uma representação invariante a rotação, escala e distorções de perspectiva. Enquanto um método é adequado a objetos texturizados, tanto planares como não-planares, o outro método foca em objetos planares não texturizados. Avaliações qualitativas e quantitativas dos métodos propostos são realizadas, mostrando que eles podem obter resultados melhores que alguns métodos existentes para detecção e estimação de pose de objetos, especialmente ao lidar com poses oblíquas. / Augmented Reality systems are able to perform real-time 3D registration of virtual and real objects, which consists in correctly positioning the virtual objects with respect to the real ones such that the virtual elements seem to be real. A very popular way to perform this registration is using video based object detection and tracking with planar fiducial markers. Another way of sensing the real world using video is by relying on natural features of the environment, which is more complex than using artificial planar markers. Nevertheless, natural feature detection and tracking is mandatory or desirable in some Augmented Reality application scenarios. Object detection and tracking from natural features can make use of a 3D model of the object which was obtained a priori. If such model is not available, it can be acquired using 3D reconstruction. In this case, an RGB-D sensor can be used, which has become in recent years a product of easy access to general users. It provides both a color image and a depth image of the scene and, besides being used for object modeling, it can also offer important cues for object detection and tracking in real-time. In this context, the work proposed in this document aims to investigate the use of consumer RGB-D sensors for object detection and pose estimation from natural features, with the purpose of using such techniques for developing Augmented Reality applications. Two methods based on depth-assisted rectification are proposed, which transform features extracted from the color image to a canonical view using depth data in order to obtain a representation invariant to rotation, scale and perspective distortions. While one method is suitable for textured objects, either planar or non-planar, the other method focuses on texture-less planar objects. Qualitative and quantitative evaluations of the proposed methods are performed, showing that they can obtain better results than some existing methods for object detection and pose estimation, especially when dealing with oblique poses.

Cílem diplomové práce je navrhnout levný, avšak dostatečně výkonný a univerzální systém, schopný snímání a zpracování obrazu z digitální kamery. Další částí je návrh a implementace funkcí pro zpracování obrazu a komunikace s nadřazeným systémem.

Roads are important infrastructure and are primary means of transportation. Control and maintenance of roads are substantial as the pavement surface deforms and deteriorates due to heavy load and influences of weather. Acquiring detailed information about the pavement condition is a prerequisite for proper planning of road pavement maintenance and rehabilitation. Many companies detect and localize the road pavement distresses manually, either by on-site inspection or by digitizing laser data and imagery captured by mobile mapping. The automation of road condition mapping using laser data and colour images is a challenge. Beyond that, the mapping of material properties of the road pavement surface with spectrometers has not yet been investigated. This study aims at automatic mapping of road surface condition including distress and material properties by integrating laser scanning, RGB imaging and spectrometry. All recorded data are geo-referenced by means of GNSS/ INS. Methods are developed for pavement distress detection that cope with a variety of different weather and asphalt conditions. Further objective is to analyse and map the material properties of the pavement surface using spectrometry data. No standard test data sets are available for benchmarking developments on road condition mapping. Therefore, all data have been recorded with a mobile mapping van which is set up for the purpose of this research. The concept for detecting and localizing the four main pavement distresses, i.e. ruts, potholes, cracks and patches is the following: ruts and potholes are detected using laser scanning data, cracks and patches using RGB images. For each of these pavement distresses, two or more methods are developed, implemented, compared to each other and evaluated to identify the most successful method. With respect to the material characteristics, spectrometer data of road sections are classified to indicate pavement quality. As a spectrometer registers almost a reflectivity curve in VIS, NIR and SWIR wavelength, indication of aging can be derived. After detection and localization of the pavement distresses and pavement quality classes, the road condition map is generated by overlaying all distresses and quality classes. As a preparatory step for rut and pothole detection, the road surface is extracted from mobile laser scanning data based on a height jump criterion. For the investigation on rut detection, all scanlines are processed. With an approach based on iterative 1D polynomial fitting, ruts are successfully detected. For streets with the width of 6 m to 10 m, a 6th order polynomial is found to be most suitable. By 1D cross-correlation, the centre of the rut is localized. An alternative method using local curvature shows a high sensitivity to the shape and width of a rut and is less successful. For pothole detection, the approach based on polynomial fitting generalized to two dimensions. As an alternative, a procedure using geodesic morphological reconstruction is investigated. Bivariate polynomial fitting encounters problems with overshoot at the boundary of the regions. The detection is very successful using geodesic morphology. For the detection of pavement cracks, three methods using rotation invariant kernels are investigated. Line Filter, High-pass Filter and Modified Local Binary Pattern kernels are implemented. A conceptual aspect of the procedure is to achieve a high degree of completeness. The most successful variant is the Line Filter for which the highest degree of completeness of 81.2 % is achieved. Two texture measures, the gradient magnitude and the local standard deviation are employed to detect pavement patches. As patches may differ with respect to homogeneity and may not always have a dark border with the intact pavement surface, the method using the local standard deviation is more suitable for detecting the patches. Linear discriminant analysis is utilized for asphalt pavement quality analysis and classification. Road pavement sections of ca. 4 m length are classified into two classes, namely: “Good” and “Bad” with the overall accuracy of 77.6 %. The experimental investigations show that the developed methods for automatic distress detection are very successful. By 1D polynomial fitting on laser scanlines, ruts are detected. In addition to ruts also pavement depressions like shoving can be revealed. The extraction of potholes is less demanding. As potholes appear relatively rare in the road networks of a city, the road segments which are affected by potholes are selected interactively. While crack detection by Line Filter works very well, the patch detection is more challenging as patches sometimes look very similar to the intact surface. The spectral classification of pavement sections contributes to road condition mapping as it gives hints on aging of the road pavement. / Straßen bilden die primären Transportwege für Personen und Güter und sind damit ein wichtiger Bestandteil der Infrastruktur. Der Aufwand für Instandhaltung und Wartung der Straßen ist erheblich, da sich die Fahrbahnoberfläche verformt und durch starke Belastung und Wettereinflüsse verschlechtert. Die Erfassung detaillierter Informationen über den Fahrbahnzustand ist Voraussetzung für eine sachgemäße Planung der Fahrbahnsanierung und -rehabilitation. Viele Unternehmen detektieren und lokalisieren die Fahrbahnschäden manuell entweder durch Vor-Ort-Inspektion oder durch Digitalisierung von Laserdaten und Bildern aus mobiler Datenerfassung. Eine Automatisierung der Straßenkartierung mit Laserdaten und Farbbildern steht noch in den Anfängen. Zudem werden bisher noch nicht die Alterungszustände der Asphaltdecke mit Hilfe der Spektrometrie bewertet. Diese Studie zielt auf den automatischen Prozess der Straßenzustandskartierung einschließlich der Straßenschäden und der Materialeigenschaften durch Integration von Laserscanning, RGB-Bilderfassung und Spektrometrie ab. Alle aufgezeichneten Daten werden mit GNSS / INS georeferenziert. Es werden Methoden für die Erkennung von Straßenschäden entwickelt, die sich an unterschiedliche Datenquellen bei unterschiedlichem Wetter- und Asphaltzustand anpassen können. Ein weiteres Ziel ist es, die Materialeigenschaften der Fahrbahnoberfläche mittels Spektrometrie-Daten zu analysieren und abzubilden. Derzeit gibt es keine standardisierten Testdatensätze für die Evaluierung von Verfahren zur Straßenzustandsbeschreibung. Deswegen wurden alle Daten, die in dieser Studie Verwendung finden, mit einem eigens für diesen Forschungszweck konfigurierten Messfahrzeug aufgezeichnet. Das Konzept für die Detektion und Lokalisierung der wichtigsten vier Arten von Straßenschäden, nämlich Spurrillen, Schlaglöcher, Risse und Flickstellen ist das folgende: Spurrillen und Schlaglöcher werden aus Laserdaten extrahiert, Risse und Flickstellen aus RGB- Bildern. Für jede dieser Straßenschäden werden mindestens zwei Methoden entwickelt, implementiert, miteinander verglichen und evaluiert um festzustellen, welche Methode die erfolgreichste ist. Im Hinblick auf die Materialeigenschaften werden Spektrometriedaten der Straßenabschnitte klassifiziert, um die Qualität des Straßenbelages zu bewerten. Da ein Spektrometer nahezu eine kontinuierliche Reflektivitätskurve im VIS-, NIR- und SWIR-Wellenlängenbereich aufzeichnet, können Merkmale der Asphaltalterung abgeleitet werden. Nach der Detektion und Lokalisierung der Straßenschäden und der Qualitätsklasse des Straßenbelages wird der übergreifende Straßenzustand mit Hilfe von Durchschlagsregeln als Kombination aller Zustandswerte und Qualitätsklassen ermittelt. In einem vorbereitenden Schritt für die Spurrillen- und Schlaglocherkennung wird die Straßenoberfläche aus mobilen Laserscanning-Daten basierend auf einem Höhensprung-Kriterium extrahiert. Für die Untersuchung zur Spurrillen-Erkennung werden alle Scanlinien verarbeitet. Mit einem Ansatz, der auf iterativer 1D-Polynomanpassung basiert, werden Spurrillen erfolgreich erkannt. Für eine Straßenbreite von 8-10m erweist sich ein Polynom sechsten Grades als am besten geeignet. Durch 1D-Kreuzkorrelation wird die Mitte der Spurrille erkannt. Eine alternative Methode, die die lokale Krümmung des Querprofils benutzt, erweist sich als empfindlich gegenüber Form und Breite einer Spurrille und ist weniger erfolgreich. Zur Schlaglocherkennung wird der Ansatz, der auf Polynomanpassung basiert, auf zwei Dimensionen verallgemeinert. Als Alternative wird eine Methode untersucht, die auf der Geodätischen Morphologischen Rekonstruktion beruht. Bivariate Polynomanpassung führt zu Überschwingen an den Rändern der Regionen. Die Detektion mit Hilfe der Geodätischen Morphologischen Rekonstruktion ist dagegen sehr erfolgreich. Zur Risserkennung werden drei Methoden untersucht, die rotationsinvariante Kerne verwenden. Linienfilter, Hochpassfilter und Lokale Binäre Muster werden implementiert. Ein Ziel des Konzeptes zur Risserkennung ist es, eine hohe Vollständigkeit zu erreichen. Die erfolgreichste Variante ist das Linienfilter, für das mit 81,2 % der höchste Grad an Vollständigkeit erzielt werden konnte. Zwei Texturmaße, nämlich der Betrag des Grauwert-Gradienten und die lokale Standardabweichung werden verwendet, um Flickstellen zu entdecken. Da Flickstellen hinsichtlich der Homogenität variieren können und nicht immer eine dunkle Grenze mit dem intakten Straßenbelag aufweisen, ist diejenige Methode, welche die lokale Standardabweichung benutzt, besser zur Erkennung von Flickstellen geeignet. Lineare Diskriminanzanalyse wird zur Analyse der Asphaltqualität und zur Klassifikation benutzt. Straßenabschnitte von ca. 4m Länge werden zwei Klassen („Gut“ und „Schlecht“) mit einer gesamten Accuracy von 77,6 % zugeordnet. Die experimentellen Untersuchungen zeigen, dass die entwickelten Methoden für die automatische Entdeckung von Straßenschäden sehr erfolgreich sind. Durch 1D Polynomanpassung an Laser-Scanlinien werden Spurrillen entdeckt. Zusätzlich zu Spurrillen werden auch Unebenheiten des Straßenbelages wie Aufschiebungen detektiert. Die Extraktion von Schlaglöchern ist weniger anspruchsvoll. Da Schlaglöcher relativ selten in den Straßennetzen von Städten auftreten, werden die Straßenabschnitte mit Schlaglöchern interaktiv ausgewählt. Während die Rissdetektion mit Linienfiltern sehr gut funktioniert, ist die Erkennung von Flickstellen eine größere Herausforderung, da Flickstellen manchmal der intakten Straßenoberfläche sehr ähnlich sehen. Die spektrale Klassifizierung der Straßenabschnitte trägt zur Straßenzustandsbewertung bei, indem sie Hinweise auf den Alterungszustand des Straßenbelages liefert.

<p>У овој докторској дисертацији извршен је преглед постојећих метода мерења угаоног положаја и дат је предлог нове методе за мерење апсолутног угаоног положаја. Предложена мерна метода заснива се на примени трансформације боје објекта из Декартовог RGB простора боја у неки од цилиндричних, кориснички оријентисаних, простора боја (HSV, HSI, HLS). На бази предложене мерне методе конструисан је сензор апсолутног угаоног положаја који се састоји од три оптичка рефлексиона сензора и штампаног шаблона са сивом скалом. Тачност, поновљивост и резолуција мерења, постигнути приликом тестирања сензора су &plusmn;1 &deg;, &plusmn;0,3 &deg; и 0,1 &deg;.</p> / <p>U ovoj doktorskoj disertaciji izvršen je pregled postojećih metoda merenja ugaonog položaja i dat je predlog nove metode za merenje apsolutnog ugaonog položaja. Predložena merna metoda zasniva se na primeni transformacije boje objekta iz Dekartovog RGB prostora boja u neki od cilindričnih, korisnički orijentisanih, prostora boja (HSV, HSI, HLS). Na bazi predložene merne metode konstruisan je senzor apsolutnog ugaonog položaja koji se sastoji od tri optička refleksiona senzora i štampanog šablona sa sivom skalom. Tačnost, ponovljivost i rezolucija merenja, postignuti prilikom testiranja senzora su &plusmn;1 &deg;, &plusmn;0,3 &deg; i 0,1 &deg;.</p> / <p>In this doctoral thesis a review of existing methods for angular position<br />measurement is conducted and a new method for measuring absolute<br />angular position is proposed. The proposed measurement method is based<br />on the use of object color transformation from Cartesian RGB color space to<br />one of the user-oriented cylindrical color space (HSV, HSI, HLS). Оn the<br />basis of the proposed measurement method, absolute angular position<br />sensor consisting of three optical reflective sensors and a grayscale printed<br />pattern is constructed. Accuracy, repeatability and resolution of<br />measurement using proposed sensor were &plusmn; 1 &deg;, &plusmn; 0.3 &deg; and 0.1 &deg;.</p>

Para efetivamente tratar uma infecção, é necessário que o antibiótico possua atividade antimicrobiana adequada e seja capaz de inibir o crescimento do microrganismo patogênico. O doseamento microbiológico é uma metodologia indicada para a análise do antimicrobiano de forma simples, quando comparado com outras metodologias. A Food and Drug Administration (FDA) tem encorajado uma abordagem proativa para introduzir inovações e benefícios associados ao processo de produção farmacêutica. A Qualidade por Design Analítico (AQbD) ajuda no desenvolvimento de métodos analíticos robustos e de baixo custo, que são aplicáveis durante todo ciclo de vida do produto. Os métodos microbiológicos tradicionais, de forma geral, apresentam baixa reprodutibilidade e alta incerteza. Desta forma, justifica-se o desenvolvimento de métodos microbiológicos alternativos para a análise de antimicrobianos empregando-se os conceitos de Qualidade por Design Analítico, com a finalidade de melhorar a reprodutibilidade e reduzir a incerteza final. O objetivo deste trabalho foi aplicar o conceito de Qualidade por Design Analítico (AQbD) no desenvolvimento de método colorimétrico para análise de sulfato de neomicina. O sulfato de neomicina é um antimicrobiano aminoglicosídeo amplamente empregado no tratamento de infecções cutâneas ou mucosas, tais como queimaduras, úlceras, e dermatites infecciosas. Métodos cromatográficos como a cromatografia líquida de alta eficiência em fase reversa, de pareamento iônico ou cromatografia iônica com derivatização (pré ou pós-coluna) são utilizados para a análise de aminoglicosídeos, inclusive sulfato de neomicina. Contudo, de acordo com as farmacopeias, o método microbiológico é o método analítico de escolha para a análise de sulfato de neomicina e outros aminoglicosídeos. A análise colorimétrica é um método amplamente utilizado para a detecção e quantificação de diferentes substâncias, incluindo o crescimento microbiano em estudos de eficácia terapêutica. Neste trabalho, propomos o uso de resazurina como marcador colorimétrico. O indicador sofre uma reação de oxido-redução na qual altera a coloração em resposta à redução química resultante do crescimento celular. O uso de microplacas para a análise colorimétrica é uma alternativa ao método realizado em tubos de ensaio. Uma alternativa ao uso de espectrofotômetros para a análise colorimétrica é o uso de aparelhos smartphones, pois são equipados com CPUs rápidas, câmeras de alta resolução e sensores de imagem. O processamento da imagem captada pela câmera do dispositivo é utilizado como um analisador colorimétrico. Portanto, a aplicação dos conceitos de Qualidade por Design Analítico (AQbD) possibilitou o desenvolvimento racional de método microbiológico colorimétrico para análise de sulfato de neomicina. / To effectively treat an infection, the antibiotic must have adequate antimicrobial activity and be capable of inhibiting the growth of the pathogenic microorganism. The microbiological assay is an indicated methodology for the analysis of the antimicrobial in a simple way, when compared with other methodologies. The Food and Drug Administration (FDA) has encouraged a proactive approach to introducing innovations and benefits associated with the pharmaceutical production process. Analytical Design Quality (AQbD) assists in the development of robust, low cost analytical methods that are applicable throughout the product life cycle. Traditional microbiological methods, in general, have low reproducibility and high uncertainty. Thus, it is justified the development of alternative microbiological methods for the analysis of antimicrobials using the concepts of Quality by Analytical Design, in order to improve reproducibility and reduce final uncertainty. The objective of this work was to apply the concept of Quality by Analytical Design (AQbD) in the development of a colorimetric method for the analysis of neomycin sulfate. Neomycin Sulfate is an aminoglycoside antimicrobial widely used in the treatment of cutaneous or mucosal infections, such as burns, ulcers, and infectious dermatitis. Chromatographic methods such as reverse phase high performance liquid chromatography, ion-pairing or ion chromatography with derivatization (pre or post-column) are used for the analysis of aminoglycosides, including neomycin sulfate. However, according to pharmacopoeias, the microbiological method is the analytical method of choice for the analysis of neomycin sulphate and other aminoglycosides. Colorimetric analysis is a widely used method for the detection and quantification of different substances, including microbial growth in studies of therapeutic efficacy. In this work, we propose the use of resazurin as a colorimetric marker. The indicator undergoes an oxidation-reduction reaction in which it alters the coloration in response to the chemical reduction resulting from cell growth. The use of microplates for colorimetric analysis is an alternative to the method carried out in test tubes. An alternative to the use of spectrophotometers for colorimetric analysis is the use of smartphones because they are equipped with fast CPUs, high resolution cameras and image sensors. The image processing captured by the device\'s camera is used as a colorimetric analyzer. Therefore, the application of the concepts of Quality by Analytical Design (AQbD) allowed the rational development of a microbiological colorimetric method for analysis of neomycin sulfate.

A análise da retina permite o diagnostico de muitas patologias relacionadas ao olho humano. A qualidade da imagem e um fator importante já que o médico normalmente examina os pequenos vasos da retina e a sua coloração. O equipamento normalmente utilizado para a visualização da retina e o retinógrafo digital, que utiliza sensor colorido com filtro de Bayer e luz (flash) branca. No entanto, esse filtro causa perda na resolução espacial, uma vez que e necessário um processo de interpolação matemática para a formação da imagem. Com o objetivo de melhorar a qualidade da imagem da retina, um retinógrafo com câmera CCD monocromática de alta resolução foi desenvolvido. Nele, as imagens coloridas são geradas pela combinação dos canais monocromáticos R (vermelho), G (verde) e B (azul), adquiridos com o chaveamento da iluminação do olho com LED vermelho, verde e azul, respectivamente. Entretanto, o pequeno período entre os flashes pode causar desalinhamento entre os canais devido a pequenos movimentos do olho. Assim, este trabalho apresenta uma técnica de registro de imagens, baseado em correlação de fase no domínio da frequência, para realizar precisamente o alinhamento dos canais RGB no processo de geração de imagens coloridas da retina. A validação do método foi realizada com um olho mecânico (phantom) para a geração de 50 imagens desalinhadas que foram corrigidas pelo método proposto e comparadas com as imagens alinhadas obtidas como referência (ground-truth). Os resultados mostraram que retinógrafo com câmera monocromática e o método de registro proposto nesse trabalho podem produzir imagens coloridas da retina com alta resolução espacial, sem a perda de qualidade intrínseca às câmeras CCD coloridas que utilizam o filtro de Bayer. / The analysis of retina allows the diagnostics of several pathologies related to the human eye. Image quality is an important factor since the physician often examines the small vessels of the retina and its color. The device usually used to observe the retina is the fundus camera, which uses color sensor with Bayer filter and white light. However, this filter causes loss of spatial resolution, since it is necessary a mathematical interpolation process to create the final image. Aiming at improving the retina image quality, a fundus camera with monochromatic CCD camera was developed. In this device, color images are generated by combining the monochromatic channels R (red), G (green) and B (blue), which were acquired by switching the eye illumination with red, green and blue light, respectively. However, the short period between the flashes may cause misalignment among the channels because of the small movements of the eye. Thus, this work presents an image registration technique based on phase correlation in the frequency domain, for accurately aligning the RGB channels on the process of generating retina color images. Validation of the method was performed by using a mechanical eye (phantom) for generating 50 misaligned images, which were aligned by the proposed method and compared to the aligned images obtained as references (ground-truth). Results showed that the fundus camera with monochromatic camera and the method proposed in this work can produce high spatial resolution images without the loss of quality intrinsic to color CCD cameras that uses Bayer filter.